CIRCL/cwe-parent-vulnerability-classification-bert-base-uncased

README.md

@@ -0,0 +1,101 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: cwe-parent-vulnerability-classification-bert-base-uncased
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# cwe-parent-vulnerability-classification-bert-base-uncased
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.9385
+- Accuracy: 0.4270
+- F1 Macro: 0.2048
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.2751        | 1.0   | 25   | 3.3057          | 0.0112   | 0.0019   |
+| 3.1518        | 2.0   | 50   | 3.1378          | 0.0449   | 0.0337   |
+| 3.0997        | 3.0   | 75   | 3.2138          | 0.0674   | 0.0376   |
+| 2.9858        | 4.0   | 100  | 3.1921          | 0.1348   | 0.0806   |
+| 2.9764        | 5.0   | 125  | 3.1470          | 0.2584   | 0.1308   |
+| 2.8564        | 6.0   | 150  | 3.2075          | 0.3708   | 0.1465   |
+| 2.8474        | 7.0   | 175  | 3.1799          | 0.3596   | 0.1653   |
+| 2.7354        | 8.0   | 200  | 3.1618          | 0.3483   | 0.1412   |
+| 2.6452        | 9.0   | 225  | 3.1248          | 0.3258   | 0.1531   |
+| 2.5802        | 10.0  | 250  | 3.1154          | 0.3371   | 0.1488   |
+| 2.5078        | 11.0  | 275  | 3.1547          | 0.3820   | 0.1712   |
+| 2.4203        | 12.0  | 300  | 3.1410          | 0.3483   | 0.1549   |
+| 2.3624        | 13.0  | 325  | 3.1409          | 0.4045   | 0.1776   |
+| 2.3642        | 14.0  | 350  | 3.0964          | 0.2809   | 0.1496   |
+| 2.2259        | 15.0  | 375  | 3.0960          | 0.3708   | 0.1904   |
+| 2.1874        | 16.0  | 400  | 3.0170          | 0.3146   | 0.1653   |
+| 2.15          | 17.0  | 425  | 3.0944          | 0.3146   | 0.1452   |
+| 2.1051        | 18.0  | 450  | 3.0225          | 0.3258   | 0.1807   |
+| 1.988         | 19.0  | 475  | 3.0687          | 0.3820   | 0.1539   |
+| 1.9716        | 20.0  | 500  | 3.0054          | 0.3820   | 0.1675   |
+| 1.9034        | 21.0  | 525  | 2.9834          | 0.3820   | 0.1985   |
+| 1.8538        | 22.0  | 550  | 3.0251          | 0.3933   | 0.1942   |
+| 1.8294        | 23.0  | 575  | 3.0231          | 0.3708   | 0.1579   |
+| 1.7436        | 24.0  | 600  | 2.9719          | 0.4045   | 0.1976   |
+| 1.7088        | 25.0  | 625  | 2.9701          | 0.4157   | 0.2138   |
+| 1.7028        | 26.0  | 650  | 2.9724          | 0.4607   | 0.2250   |
+| 1.6962        | 27.0  | 675  | 2.9385          | 0.4270   | 0.2048   |
+| 1.5973        | 28.0  | 700  | 2.9636          | 0.4494   | 0.1904   |
+| 1.5754        | 29.0  | 725  | 2.9441          | 0.5393   | 0.2116   |
+| 1.5279        | 30.0  | 750  | 2.9785          | 0.5506   | 0.2373   |
+| 1.5802        | 31.0  | 775  | 2.9711          | 0.5618   | 0.2346   |
+| 1.4479        | 32.0  | 800  | 2.9884          | 0.5730   | 0.2335   |
+| 1.484         | 33.0  | 825  | 3.0117          | 0.5730   | 0.2550   |
+| 1.4243        | 34.0  | 850  | 2.9759          | 0.5843   | 0.2408   |
+| 1.4473        | 35.0  | 875  | 2.9626          | 0.5955   | 0.2692   |
+| 1.3875        | 36.0  | 900  | 2.9673          | 0.5843   | 0.2342   |
+| 1.4214        | 37.0  | 925  | 2.9887          | 0.5843   | 0.2564   |
+| 1.373         | 38.0  | 950  | 2.9894          | 0.6067   | 0.2728   |
+| 1.3472        | 39.0  | 975  | 2.9805          | 0.5730   | 0.2311   |
+| 1.336         | 40.0  | 1000 | 2.9836          | 0.5843   | 0.2439   |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.2

config.json

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   "max_position_embeddings": 512,

emissions.csv

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+2025-09-03T13:44:15,codecarbon,e223fd7a-695a-4203-b04b-c12e5b394872,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,371.78134503099136,0.006129368180714177,1.6486486647691367e-05,42.5,332.9863602842321,94.34468507766725,0.00438576165376548,0.044108631120195696,0.009734692286451092,0.058229085060412265,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-71-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.5858268737793,machine,N,1.0

metrics.json

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+{
+    "eval_loss": 2.938542127609253,
+    "eval_accuracy": 0.42696629213483145,
+    "eval_f1_macro": 0.20475524132174594,
+    "eval_runtime": 0.3212,
+    "eval_samples_per_second": 277.068,
+    "eval_steps_per_second": 9.339,
+    "epoch": 40.0
+}

model.safetensors

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